EE 353 (was EE 317)

EE 353, Continuous- and Discrete-time Signals and Systems, is a core course
taken by all computer engineering students that provides exposure to a variety
of topics in linear systems. The material in this course is needed for further
study in image processing and data communications, both of which are major
areas of specialization within the computer engineering curriculum.

This course is divided into three main sections - continuous-time linear system
analysis, sampling and reconstruction, and discrete-time (digital) linear system
analysis. Although the material covered in the first and last sections is similar,
fundamental differences between continuous- and discrete-time exist. One of
the goals of this course is to make the student aware of these differences.

The first part of the course discusses continuous-time linear system analysis.
It begins with basic time-domain mathematical descriptions of various signals
and systems. The bulk of the analysis, however, is in frequency domain approaches
such as the Fourier Series and the Fourier Transform. Applications such as
modulation and multiplexing are understood much easier using frequency-domain
analysis approaches.

The middle part of the course deals with the bridge between continuous- and
discrete-time, namely signal sampling and reconstruction. Theoretical and practical
approaches to sampling/reconstruction are covered. Finally the Nyquist sampling
theorem, which is the key to all digital signals, is developed. At this point,
students are ready to study discrete-time systems.

The final part of this course revisits system analysis, although now discrete-time
(or digital) systems are considered. As in the continuous-time case, both time-domain
and frequency-domain approaches to the analysis problem are discussed. The
course ends with select topics in the z-transform, which is the digital counterpart
to the Laplace transform.